Category Archives: Personal statements

CASyM 2015 Summer School lectures available on video

A collection of 12 educational lectures on Systems Medicine, held during the 2015 CASyM Summer School, is available under the follwoing link:
https://www.youtube.com/playlist?list=PLL7sagKe8dNMUpDbhx1_cML5OiqKtucQR

Additional information on the CASyM Summer SChool can be found here:
https://www.casym.eu/events?cmd=showDetail&id=329
https://www.casym.eu/index.php?index=90

 

 

 

A systems biology approach reveals the physiological origin of hepatic steatosis induced by liver X receptor activation

Liver X receptor (LXR) agonists exert potent antiatherosclerotic actions but simultaneously induce excessive triglyceride (TG) accumulation in the liver. To obtain a detailed insight into the underlying mechanism of hepatic TG accumulation, we used a novel computational modeling approach called analysis of dynamic adaptations in parameter trajectories (ADAPT). We revealed that both input and output fluxes to hepatic TG content are considerably induced on LXR activation and that in the early phase of LXR agonism, hepatic steatosis results from only a minor imbalance between the two. It is generally believed that LXR-induced hepatic steatosis results from increased de novo lipogenesis (DNL). In contrast, ADAPT predicted that the hepatic influx of free fatty acids is the major contributor to hepatic TG accumulation in the early phase of LXR activation. Qualitative validation of this prediction showed a 5-fold increase in the contribution of plasma palmitate to hepatic monounsaturated fatty acids on acute LXR activation, whereas DNL was not yet significantly increased. This study illustrates that complex effects of pharmacological intervention can be translated into distinct patterns of metabolic regulation through state-of-the-art mathematical modeling.

Hijmans BS, Tiemann CA, Grefhorst A, Boesjes M, van Dijk TH, Tietge UJ, Kuipers F, van Riel NA, Groen AK, Oosterveer MH. A systems biology approach reveals the physiological origin of hepatic steatosis induced by liver X receptor activation. FASEB Journal, 2014 Dec 4. [Epub ahead of print]

http://www.ncbi.nlm.nih.gov/pubmed/25477282

http://www.fasebj.org/content/early/2014/12/03/fj.14-254656.long

Personal statement about CASyM by Olaf Wolkenhauer, SBI Rostock

Wolkenhauer_II “If anyone is in doubt about what Systems Medicine is, there is a simple answer: ‘Systems Medicine is an opportunity – an opportunity for clinical researchers to join forces with biologists, computer scientists and mathematicians to address their questions – using a multidisciplinary, integrative approach.’

And if anyone wonders what CASyM is: “CASyM is an invitation to make Systems Medicine a reality, in Europe.”‘

Olaf Wolkenhauer

Picture: private

Walter Kolch, NUID UCD about CASyM and bridging the gap between the clinic and clinical research and systems biology technologies

WKolchAs a systems biology institute where wet lab scientists and computational biologists work together, we know very well how systems biology can form bridges between different fields, and how computational modeling can help with questions that are hard to answer with traditional (wet lab) research techniques. However, we feel that systems biology could have a more translational impact, through systems medicine. Computational modeling could for instance make clinical trials more efficient and cheaper.

Hans Westerhoff about: The consensus metabolic map: towards individualized medicine, based on genomics, nutritional and lifestyle information

The community-driven reconstruction of human metabolism (3 March 2013, Nature Biotechnology, nbt.2488) was a significant step for some 35 systems biologists, but an enormous leap for mankind. (Probably) for the first time in the history of the universe, a species understands how it can make itself, in terms of its molecular components. Where the complete genome sequence in 2000 was an abstract collection of information about the human species, this map provides the first comprehensive and consensus, functional interpretation of that genome.

A short personal statement why Systems Medicine and CASyM is important from Silvio Parodi, UNIGE.

I will touch two different aspects.

1. With reference to the CASyM goals, I found potentially connected with them and conceptually very advanced the Watson / IBM / Sloan Kettering project: IBM works on the project by more than four years. Apparently they are strongly committed.

The idea of supporting the clinician in a transition from an opinion-based (a medical doctor capable of being aware of a limited number of data) toward the utilization of a much larger spectrum of data conducing to an evidence-based and more personalized medicine, seems very intriguing.

Watson is capable of “understanding” directly the human language.

Rob Diemel, ZonMw – Personal statement about CASyM

Diemel“We’ve come to realize that diseases can be effectively countered only if we have a thorough understanding of life, both in health and disease. This causes a change in thinking about medicine. Clinicians will need to have access to molecular knowledge for use in diagnosis and treatment of individual patients. Patients and pharmaceutical companies will need to get access to drugs that have known and precise effects. Systems Medicine is a way to obtain such information. The basis is already here, since data are nowadays massively available (through –omics techniques and cell cultures) and mechanistic models are being developed. The next step is the wide application of Systems Medicine as a standard way of research in clinic, healthcare and industry.

Rudi Balling, LCSB – Personal statement on Systems Medicine and CASyM

Balling_2013Interdisciplinarity is easy to talk about, but much more difficult to implement. This is also one of the challenges of modern medicine. In order to develop new strategies for prevention and therapy of diseases, we need to understand the pathogenesis of the disease. This, however, is not possible anymore with the classical approach of experimental biology or clinical research. We urgently need to bridge the gap between the different disciplines; the ones that are involved in dissecting the perturbation of disease networks but also the ones helping to translate the insights gained by modern –omics technologies as well as pathway and network reconstruction into clinical decision support systems. This is where CASyM will play an essential role.